R/OceanTracer-package.R

In OceanTracer: Marine Source Unmixing Toolkit

#' @title A comprehensive package for marine source unmixing
#' 
#' @description
#' Advanced apportionment toolkit designed specifically for marine biogeochemistry, coastal tracing, and oceanographic sediment transport. It reconstructs the provenance of particulate matter and marine sediments by unmixing isotopic and elemental signatures. The package introduces marine-optimized linear variability propagation alongside automated baseline corrections for compound-specific isotopes.
#' @author
#' **Authors:**
#' * Esther Cepeda (Maintainer) <cepeda.esther@hotmail.com>
#' * Maarten Wynants
#' * Ivan Lizaga <lizaga.ivan10@gmail.com>
#' 
#' **Contributors:**
#' * Samuel Bodé, Pascal Boeckx, Jan Vanaverbeke, Ulrike Braeckman, Aiming Liang, Borja Latorre, Leticia Gaspar, Ana Navas, Vince Q Vu
#'
#' @md
#'
#' @section Tool development:
#'
#' - OceanTracers born from a combine expertise between unmixing experts and
#'   marine scientist including the state-of-the-art techniques implemented in
#'   sediment tracing and the up to date techniques used in marine tracing.
#'
#' @keywords internal
#' @return No return value, package overview.
#' 
#' @import ggplot2
#' @importFrom stats lm.fit coef rt rnorm runif prcomp predict cor hclust as.dist cutree as.formula kruskal.test aggregate sd quantile qchisq var dist complete.cases median
#' @importFrom utils txtProgressBar setTxtProgressBar head tail
#' @importFrom grDevices colorRampPalette rainbow
#' @importFrom graphics par title
#' @importFrom magrittr %>%
#' @importFrom dplyr mutate select filter group_by ungroup across everything rename_with select_if rowwise
#' @importFrom tidyr unnest
#' @importFrom tidyselect starts_with ends_with
#' @importFrom reshape2 melt
#' @importFrom Ternary TernaryPlot TernaryPoints
#' @importFrom klaR greedy.wilks
#' @importFrom plotly plot_ly add_markers
#'
#' @examples
#' \donttest{
#' # 1. Load built-in example dataset
#' data_path <- system.file(
#'    "extdata", 
#'    "ArtificialMixtureAminoAcidData.csv",
#'    package = "OceanTracer"
#' )
#' data_AM <- read.csv(data_path)
#' 
#' # 2. Color palette setup
#' my_cols <- c(
#'    S1 = "#56B4E9", 
#'    S2 = "#509E73", 
#'    S3 = "#E6925F", 
#'    Mx = "purple"
#' )
#' 
#' # 3. Generate initial diagnostic plots
#' Graph_boxplots(data_AM, tracers = 1:12, ncol = 3, colors = my_cols)
#' Correlation_Chart(data_AM, tracers = 1:12, mixtures = TRUE, colors = my_cols)
#' }
"_PACKAGE"